Biclustering in Biomedical Data Analysis: Algorithms and Applications

Biclustering, the discovery of sets of objects with coherent values/patterns on subsets of features, was shown to be key to unravel and characterize informative regions (biclusters) within matricial, time series and network data, in a wide-set of applications in biomedical and social data analysis. Particularly in biomedical problems, where groups of genes or patients tend to be only meaningfully related on a subset of the sampled/monitored conditions.